水下无人系统学报2025，Vol.33Issue(2)：204-211,8.DOI:10.11993/j.issn.2096-3920.2025-0003
基于小波变换特征增强的水下目标检测方法
Underwater Object Detection Method with Enhanced Wavelet Transform Features
摘要
Abstract
The complex and unique underwater environment results in low-quality underwater images,characterized by low contrast,blurriness,and underwater degradation,which significantly affects the capabilities of underwater object detection.To address this issue,this paper proposed an underwater object detection method with enhanced wavelet transform features.The paper introduced discrete wavelet transform(DWT)to decompose the multi-level features extracted by the deep learning framework into high-and low-frequency components.These frequency domain feature components were then interactively enhanced using a frequency domain interaction module based on the attention mechanism designed in this work,optimizing the ability of feature expression.The enhanced features were subsequently fed into the object detection network to improve the object detection performance.Experimental results demonstrate that the proposed underwater object detection method outperforms conventional object detection methods,significantly improving the ability to detect objects in underwater environments.关键词
水下目标检测/深度学习/小波变换Key words
underwater object detection/deep learning/wavelet transform分类
武器工业引用本文复制引用
魏楠,杨万扣,周伟杰,姜龙玉..基于小波变换特征增强的水下目标检测方法[J].水下无人系统学报,2025,33(2):204-211,8.基金项目
国家自然科学基金项目(61871124、61876037). （61871124、61876037）
